diff --git a/.circleci/config.yml b/.circleci/config.yml
index 8aa7dc9855b..a804188cbb5 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -315,20 +315,22 @@ jobs:
           paths:
             - conda
             - env
-      - run:
-          # Here we create an envlist file that contains some env variables that we want the docker container to be aware of.
-          # Normally, the CIRCLECI variable is set and available on all CI workflows: https://circleci.com/docs/2.0/env-vars/#built-in-environment-variables.
-          # They're available in all the other workflows (OSX and Windows).
-          # But here, we're running the unittest_linux_gpu workflows in a docker container, where those variables aren't accessible.
-          # So instead we dump the variables we need in env.list and we pass that file when invoking "docker run".
-          name: export CIRCLECI env var
-          command: echo "CIRCLECI=true" >> ./env.list
+#      - run:
+#          # Here we create an envlist file that contains some env variables that we want the docker container to be aware of.
+#          # Normally, the CIRCLECI variable is set and available on all CI workflows: https://circleci.com/docs/2.0/env-vars/#built-in-environment-variables.
+#          # They're available in all the other workflows (OSX and Windows).
+#          # But here, we're running the unittest_linux_gpu workflows in a docker container, where those variables aren't accessible.
+#          # So instead we dump the variables we need in env.list and we pass that file when invoking "docker run".
+#          name: export CIRCLECI env var
+#          command: echo "CIRCLECI=true" >> ./env.list
       - run:
           name: Install torchrl
+#          command: bash .circleci/unittest/linux/scripts/install.sh
           command: docker run -t --gpus all -v $PWD:$PWD -w $PWD -e UPLOAD_CHANNEL -e CU_VERSION "${image_name}" .circleci/unittest/linux/scripts/install.sh
       - run:
           name: Run tests
-          command: docker run --env-file ./env.list -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/run_test.sh
+          command: bash .circleci/unittest/linux/scripts/run_test.sh
+#          command: docker run --env-file ./env.list -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/run_test.sh
       - run:
           name: Post Process
           command: docker run -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/post_process.sh
@@ -368,20 +370,22 @@ jobs:
           paths:
             - conda
             - env
-      - run:
-          # Here we create an envlist file that contains some env variables that we want the docker container to be aware of.
-          # Normally, the CIRCLECI variable is set and available on all CI workflows: https://circleci.com/docs/2.0/env-vars/#built-in-environment-variables.
-          # They're available in all the other workflows (OSX and Windows).
-          # But here, we're running the unittest_linux_gpu workflows in a docker container, where those variables aren't accessible.
-          # So instead we dump the variables we need in env.list and we pass that file when invoking "docker run".
-          name: export CIRCLECI env var
-          command: echo "CIRCLECI=true" >> ./env.list
+#      - run:
+#          # Here we create an envlist file that contains some env variables that we want the docker container to be aware of.
+#          # Normally, the CIRCLECI variable is set and available on all CI workflows: https://circleci.com/docs/2.0/env-vars/#built-in-environment-variables.
+#          # They're available in all the other workflows (OSX and Windows).
+#          # But here, we're running the unittest_linux_gpu workflows in a docker container, where those variables aren't accessible.
+#          # So instead we dump the variables we need in env.list and we pass that file when invoking "docker run".
+#          name: export CIRCLECI env var
+#          command: echo "CIRCLECI=true" >> ./env.list
       - run:
           name: Install torchrl
-          command: docker run -t --gpus all -v $PWD:$PWD -w $PWD -e UPLOAD_CHANNEL -e CU_VERSION "${image_name}" .circleci/unittest/linux_optdeps/scripts/install.sh
+#          command: bash .circleci/unittest/linux_optdeps/scripts/install.sh
+          command: docker run -t --gpus all -v $PWD:$PWD -w $PWD -e UPLOAD_CHANNEL -e CU_VERSION "${image_name}" .circleci/unittest/linux/scripts/install.sh
       - run:
           name: Run tests
-          command: docker run --env-file ./env.list -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux_optdeps/scripts/run_test.sh
+          command: bash .circleci/unittest/linux_optdeps/scripts/run_test.sh
+#          command: docker run --env-file ./env.list -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/run_test.sh
       - run:
           name: Post Process
           command: docker run -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux_optdeps/scripts/post_process.sh
@@ -468,20 +472,22 @@ jobs:
           paths:
             - conda
             - env
-      - run:
-          # Here we create an envlist file that contains some env variables that we want the docker container to be aware of.
-          # Normally, the CIRCLECI variable is set and available on all CI workflows: https://circleci.com/docs/2.0/env-vars/#built-in-environment-variables.
-          # They're availble in all the other workflows (OSX and Windows).
-          # But here, we're running the unittest_linux_gpu workflows in a docker container, where those variables aren't accessible.
-          # So instead we dump the variables we need in env.list and we pass that file when invoking "docker run".
-          name: export CIRCLECI env var
-          command: echo "CIRCLECI=true" >> ./env.list
+#      - run:
+#          # Here we create an envlist file that contains some env variables that we want the docker container to be aware of.
+#          # Normally, the CIRCLECI variable is set and available on all CI workflows: https://circleci.com/docs/2.0/env-vars/#built-in-environment-variables.
+#          # They're available in all the other workflows (OSX and Windows).
+#          # But here, we're running the unittest_linux_gpu workflows in a docker container, where those variables aren't accessible.
+#          # So instead we dump the variables we need in env.list and we pass that file when invoking "docker run".
+#          name: export CIRCLECI env var
+#          command: echo "CIRCLECI=true" >> ./env.list
       - run:
           name: Install torchrl
-          command: docker run -t --gpus all -v $PWD:$PWD -w $PWD -e UPLOAD_CHANNEL -e CU_VERSION "${image_name}" .circleci/unittest/linux_stable/scripts/install.sh
+#          command: bash .circleci/unittest/linux_stable/scripts/install.sh
+          command: docker run -t --gpus all -v $PWD:$PWD -w $PWD -e UPLOAD_CHANNEL -e CU_VERSION "${image_name}" .circleci/unittest/linux/scripts/install.sh
       - run:
           name: Run tests
-          command: docker run --env-file ./env.list -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux_stable/scripts/run_test.sh
+          command: bash .circleci/unittest/linux_stable/scripts/run_test.sh
+#          command: docker run --env-file ./env.list -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/run_test.sh
       - run:
           name: Post Process
           command: docker run -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux_stable/scripts/post_process.sh
diff --git a/.circleci/unittest/linux/scripts/setup_env.sh b/.circleci/unittest/linux/scripts/setup_env.sh
index b0cf2b465b1..d4ab971c35d 100755
--- a/.circleci/unittest/linux/scripts/setup_env.sh
+++ b/.circleci/unittest/linux/scripts/setup_env.sh
@@ -53,12 +53,13 @@ printf "* Installing dependencies (except PyTorch)\n"
 echo "  - python=${PYTHON_VERSION}" >> "${this_dir}/environment.yml"
 cat "${this_dir}/environment.yml"
 
+
 if [[ $OSTYPE == 'darwin'* ]]; then
   PRIVATE_MUJOCO_GL=glfw
-else
-  conda install -y -c conda-forge mesa
-  conda install -y -c conda-forge mesalib
+elif [ "${CU_VERSION:-}" == cpu ]; then
   PRIVATE_MUJOCO_GL=osmesa
+else
+  PRIVATE_MUJOCO_GL=egl
 fi
 
 export MUJOCO_GL=$PRIVATE_MUJOCO_GL
@@ -67,6 +68,18 @@ conda env config vars set MUJOCO_PY_MUJOCO_PATH=$root_dir/.mujoco/mujoco210 \
   MJLIB_PATH=$root_dir/.mujoco/mujoco-2.1.1/lib/libmujoco.so.2.1.1 \
   LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$root_dir/.mujoco/mujoco210/bin \
   SDL_VIDEODRIVER=dummy \
-  MUJOCO_GL=$PRIVATE_MUJOCO_GL
+  MUJOCO_GL=$PRIVATE_MUJOCO_GL \
+  PYOPENGL_PLATFORM=$PRIVATE_MUJOCO_GL
+
+# Software rendering requires GLX and OSMesa.
+if [ $PRIVATE_MUJOCO_GL == 'egl' ] || [ $PRIVATE_MUJOCO_GL == 'osmesa' ] ; then
+  yum makecache
+  yum install -y glfw
+  yum install -y glew
+  yum install -y mesa-libGL
+  yum install -y mesa-libOSMesa-devel
+  yum -y install egl-utils
+  yum -y install freeglut
+fi
 
 conda env update --file "${this_dir}/environment.yml" --prune
diff --git a/.circleci/unittest/linux_stable/scripts/setup_env.sh b/.circleci/unittest/linux_stable/scripts/setup_env.sh
index c9c6e45acc2..d4ab971c35d 100755
--- a/.circleci/unittest/linux_stable/scripts/setup_env.sh
+++ b/.circleci/unittest/linux_stable/scripts/setup_env.sh
@@ -40,7 +40,7 @@ conda activate "${env_dir}"
 
 # 3. Install mujoco
 printf "* Installing mujoco and related\n"
-mkdir $root_dir/.mujoco
+mkdir -p $root_dir/.mujoco
 cd $root_dir/.mujoco/
 wget https://github.com/deepmind/mujoco/releases/download/2.1.1/mujoco-2.1.1-linux-x86_64.tar.gz
 tar -xf mujoco-2.1.1-linux-x86_64.tar.gz
@@ -56,10 +56,10 @@ cat "${this_dir}/environment.yml"
 
 if [[ $OSTYPE == 'darwin'* ]]; then
   PRIVATE_MUJOCO_GL=glfw
-else
-  conda install -y -c conda-forge mesa
-  conda install -y -c conda-forge mesalib
+elif [ "${CU_VERSION:-}" == cpu ]; then
   PRIVATE_MUJOCO_GL=osmesa
+else
+  PRIVATE_MUJOCO_GL=egl
 fi
 
 export MUJOCO_GL=$PRIVATE_MUJOCO_GL
@@ -68,6 +68,18 @@ conda env config vars set MUJOCO_PY_MUJOCO_PATH=$root_dir/.mujoco/mujoco210 \
   MJLIB_PATH=$root_dir/.mujoco/mujoco-2.1.1/lib/libmujoco.so.2.1.1 \
   LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$root_dir/.mujoco/mujoco210/bin \
   SDL_VIDEODRIVER=dummy \
-  MUJOCO_GL=$PRIVATE_MUJOCO_GL
+  MUJOCO_GL=$PRIVATE_MUJOCO_GL \
+  PYOPENGL_PLATFORM=$PRIVATE_MUJOCO_GL
+
+# Software rendering requires GLX and OSMesa.
+if [ $PRIVATE_MUJOCO_GL == 'egl' ] || [ $PRIVATE_MUJOCO_GL == 'osmesa' ] ; then
+  yum makecache
+  yum install -y glfw
+  yum install -y glew
+  yum install -y mesa-libGL
+  yum install -y mesa-libOSMesa-devel
+  yum -y install egl-utils
+  yum -y install freeglut
+fi
 
 conda env update --file "${this_dir}/environment.yml" --prune
diff --git a/test/test_libs.py b/test/test_libs.py
index 1c9da094699..8499a35a419 100644
--- a/test/test_libs.py
+++ b/test/test_libs.py
@@ -105,7 +105,7 @@ def test_gym(env_name, frame_skip, from_pixels, pixels_only):
 
 
 @pytest.mark.skipif(not _has_dmc, reason="no dm_control library found")
-@pytest.mark.parametrize("env_name,task", [["cheetah", "run"], ["humanoid", "walk"]])
+@pytest.mark.parametrize("env_name,task", [["cheetah", "run"]])
 @pytest.mark.parametrize("frame_skip", [1, 3])
 @pytest.mark.parametrize(
     "from_pixels,pixels_only",
@@ -118,35 +118,32 @@ def test_gym(env_name, frame_skip, from_pixels, pixels_only):
 def test_dmcontrol(env_name, task, frame_skip, from_pixels, pixels_only):
     if from_pixels and (not torch.has_cuda or not torch.cuda.device_count()):
         raise pytest.skip("no cuda device")
-    env0 = DMControlEnv(
-        env_name,
-        task,
-        frame_skip=frame_skip,
-        from_pixels=from_pixels,
-        pixels_only=pixels_only,
-    )
-    torch.manual_seed(0)
-    np.random.seed(0)
-    final_seed0 = env0.set_seed(0)
-    tdreset0 = env0.reset()
-    rollout0 = env0.rollout(max_steps=50)
-    env0.close()
-    del env0
 
-    env1 = DMControlEnv(
-        env_name,
-        task,
-        frame_skip=frame_skip,
-        from_pixels=from_pixels,
-        pixels_only=pixels_only,
-    )
-    torch.manual_seed(0)
-    np.random.seed(0)
-    final_seed1 = env1.set_seed(0)
-    tdreset1 = env1.reset()
-    rollout1 = env1.rollout(max_steps=50)
-    env1.close()
-    del env1
+    tds = []
+    tds_reset = []
+    final_seed = []
+    for i in range(2):
+        env0 = DMControlEnv(
+            env_name,
+            task,
+            frame_skip=frame_skip,
+            from_pixels=from_pixels,
+            pixels_only=pixels_only,
+        )
+        torch.manual_seed(0)
+        np.random.seed(0)
+        final_seed0 = env0.set_seed(0)
+        tdreset0 = env0.reset()
+        rollout0 = env0.rollout(max_steps=50)
+        env0.close()
+        del env0
+        tds_reset.append(tdreset0)
+        tds.append(rollout0)
+        final_seed.append(final_seed0)
+
+    tdreset1, tdreset0 = tds_reset
+    rollout0, rollout1 = tds
+    final_seed0, final_seed1 = final_seed
 
     assert_allclose_td(tdreset1, tdreset0)
     assert final_seed0 == final_seed1